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trading-ai-agent-ops

Design AI trading workflows with human approval gates and audit controls.

1|Updated Mar 6, 2014
Search Tags:#automation#ai agents#risk management#market monitoring#backtesting#trading
One-click install
npx skills add https://github.com/79yuuki/dotfiles --skill trading-ai-agent-ops
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: trading-ai-agent-ops
Source: https://github.com/79yuuki/dotfiles/tree/main/claude/skills/trading-ai-agent-ops
Command: npx skills add https://github.com/79yuuki/dotfiles --skill trading-ai-agent-ops

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps prevent unsafe delegation of trading decisions to AI agents by establishing human oversight, operational controls, and auditable workflows for automated trading systems.

Core Features & Use Cases

  • AI Trading Workflow Design: Defines roles for research agents, backtesting agents, risk reviewers, execution monitors, and human approvers.
  • Risk and Operations Controls: Creates guardrails for live orders, strategy changes, monitoring, logging, and approval boundaries.
  • Use Case: Design a trading bot operation process where AI can generate hypotheses and analyze markets while humans approve capital allocation, execution changes, and risk decisions.

Quick Start

Use the trading-ai-agent-ops skill to design a safe AI agent workflow for my trading bot with approval gates and monitoring requirements.

Frequently Asked Questions about trading-ai-agent-ops

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I set up safe AI trading operations with human oversight?▼

Safe AI trading operations require role separation, audit artifacts, risk controls, approval boundaries, and operational monitoring practices to ensure human oversight over automated decision making.

What is the best way to design a trading bot workflow with approval gates?▼

Designing a trading bot workflow with approval gates involves defining roles for research agents, backtesting agents, risk reviewers, execution monitors, and human approvers to control automated decision making.

Can I use AI agents for market analysis and backtesting without delegating capital allocation?▼

Yes, AI agents can generate hypotheses and analyze markets while humans approve capital allocation, execution changes, and risk decisions through established approval boundaries and guardrails for live orders.

What risk controls do I need for automated trading systems using AI?▼

Risk controls for automated trading systems include guardrails for live orders, strategy changes, monitoring, logging, and approval boundaries to prevent unsafe delegation of trading decisions to AI agents.

Why do AI trading bots need role separation and audit artifacts?▼

AI trading bots need role separation and audit artifacts to preserve human oversight, establish operational controls, and maintain auditable workflows that prevent unsafe delegation of trading decisions to automated systems.

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